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Paper Citation Record · LEDGER

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection

As of 14 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2607.03862.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.03862 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T23:26:36.541592Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

56 of 56 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6b568863-1445-443a-a22c-f1e0015260ef · outbound

This paper cites Media forensics and deepfakes: An overview,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Media forensics and deepfakes: An overview,

Reference 1

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Observation 7a1f68b8-2103-4227-b192-debe5c7c26e9 · outbound

This paper cites A sanity check for ai-generated image detection,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection A sanity check for ai-generated image detection,

Reference 2

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Observation 0d0e1248-450b-4295-9b8c-cfe87a76653b · outbound

This paper cites Rethinking the up-sampling operations in cnn-based generative network for general- izable deepfake detection,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Rethinking the up-sampling operations in cnn-based generative network for general- izable deepfake detection,

Reference 3

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Observation fd570f64-83e1-4340-9dce-270df14b4016 · outbound

This paper cites Frequency-aware deepfake detection: improving generalizability through frequency space domain learning,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Frequency-aware deepfake detection: improving generalizability through frequency space domain learning,

Reference 4

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Observation a583a73d-c700-47ff-b7a0-41b73d089f26 · outbound

This paper cites Unmasking ai-created visual content: a review of generated images and deepfake detection technologies,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Unmasking ai-created visual content: a review of generated images and deepfake detection technologies,

Reference 5

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Observation c3c4e070-73e6-4c41-99d6-52839e83277e · outbound

This paper cites Detecting and simulating artifacts in gan fake images,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Detecting and simulating artifacts in gan fake images,

Reference 6

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Observation 11ccfc03-1661-416f-bac4-722cd5bd221f · outbound

This paper cites Fourier spectrum discrepancies in deep network generated images,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Fourier spectrum discrepancies in deep network generated images,

Reference 7

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Observation ebc3cf25-96a4-42ea-aeff-66835a75e0f7 · outbound

This paper cites Thinking in frequency: Face forgery detection by mining frequency-aware clues,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Thinking in frequency: Face forgery detection by mining frequency-aware clues,

Reference 8

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Observation 23b047a4-73e8-4d79-b120-ccdfa6180922 · outbound

This paper cites Towards universal fake image detectors that generalize across generative models,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Towards universal fake image detectors that generalize across generative models,

Reference 9

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Observation a9641739-83c5-48c3-9e06-df943f872408 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Learning transferable visual models from natural language supervision,

Reference 10

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Observation 3043fc42-e1ed-41c0-a25b-bac147939278 · outbound

This paper cites C2p-clip: Injecting category common prompt in clip to enhance generalization in deepfake detection,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection C2p-clip: Injecting category common prompt in clip to enhance generalization in deepfake detection,

Reference 11

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Observation 1b488ea7-4d75-4746-bc32-d20a27fa0e8f · outbound

This paper cites Trufor: Leveraging all-round clues for trustworthy image forgery detection and localization,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Trufor: Leveraging all-round clues for trustworthy image forgery detection and localization,

Reference 12

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Observation 954bf162-cde5-48a6-9261-5c19a9ff30b7 · outbound

This paper cites Denoising diffusion probabilistic models,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Denoising diffusion probabilistic models,

Reference 13

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Observation eee0f0f0-c101-441e-857e-566f75c07be0 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 14

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Observation 5acd6d84-4169-4299-951a-b6ef8ca04f0b · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection High- resolution image synthesis with latent diffusion models,

Reference 15

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Observation 5938cef3-5941-4058-9db0-265e03ea8e1a · outbound

This paper cites Instructpix2pix: Learning to follow image editing instructions,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Instructpix2pix: Learning to follow image editing instructions,

Reference 16

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Observation a436a798-a004-47d0-a7ba-0fda9ad82cf2 · outbound

This paper cites Adding conditional control to text-to-image diffusion models,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Adding conditional control to text-to-image diffusion models,

Reference 17

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Observation 552587f3-19c9-44ff-b1f8-223f40bcf8fc · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject- driven generation,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Dreambooth: Fine tuning text-to-image diffusion models for subject- driven generation,

Reference 18

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Observation d670aba9-03ec-4f16-a094-0556d81b2e0a · outbound

This paper cites Towards universal fake image detec- tors that generalize across generative models,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Towards universal fake image detec- tors that generalize across generative models,

Reference 19

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Observation 59cb51b3-9a93-410a-988c-7c47ad59ebf2 · outbound

This paper cites Genimage: A million-scale benchmark for detecting ai-generated image,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Genimage: A million-scale benchmark for detecting ai-generated image,

Reference 20

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Observation e6f9f74f-e827-4a9b-908d-8e1c4e593cfe · outbound

This paper cites DRCT: Diffusion recon- struction contrastive training towards universal detection of diffusion generated images,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection DRCT: Diffusion recon- struction contrastive training towards universal detection of diffusion generated images,

Reference 21

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Observation 82f2d9f3-08a8-44e3-bf75-5b35398fbb6b · outbound

This paper cites Raid: A dataset for testing the adversarial robustness of ai-generated image detectors,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Raid: A dataset for testing the adversarial robustness of ai-generated image detectors,

Reference 22

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Observation 2c182122-582d-490f-828d-edb5b9f84438 · outbound

This paper cites X2edit: Revisiting arbitrary-instruction image editing through self-constructed data and task-aware representation learning,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection X2edit: Revisiting arbitrary-instruction image editing through self-constructed data and task-aware representation learning,

Reference 23

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Observation d5cd0cb3-d88d-4700-8543-d5eaaee8fac8 · outbound

This paper cites Pico-banana-400k: A large-scale dataset for text-guided image editing,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Pico-banana-400k: A large-scale dataset for text-guided image editing,

Reference 24

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Observation 18e95ff5-38ab-42af-9929-195124a61712 · outbound

This paper cites Towards universal ai-generated image detection by variational information bottleneck net- work,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Towards universal ai-generated image detection by variational information bottleneck net- work,

Reference 25

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Observation 3d04abc6-3fad-4659-ad91-4cc4bf46c003 · outbound

This paper cites A closer look at fourier spectrum discrepancies for cnn-generated images detection,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection A closer look at fourier spectrum discrepancies for cnn-generated images detection,

Reference 26

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Observation c1542813-af92-4f24-a724-640ec1c11878 · outbound

This paper cites Breaking semantic artifacts for generalized ai-generated image detec- tion,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Breaking semantic artifacts for generalized ai-generated image detec- tion,

Reference 27

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Observation 9b775c2c-e7f4-40a3-ab38-43adb68c0eb3 · outbound

This paper cites Reducing the content bias for ai-generated image detection,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Reducing the content bias for ai-generated image detection,

Reference 28

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Observation 6648c200-f3a6-496f-ab4c-b9302d95d508 · outbound

This paper cites Determining image ori- gin and integrity using sensor noise,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Determining image ori- gin and integrity using sensor noise,

Reference 29

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Observation 8de9d88f-5106-488b-9f0f-5addb2c8f980 · outbound

This paper cites Evading deepfake-image detectors with white- and black-box attacks,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Evading deepfake-image detectors with white- and black-box attacks,

Reference 30

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Observation 9ba2fd25-8efe-4714-a482-483ab85067e9 · outbound

This paper cites Robustness of ai-image detectors: Fundamental limits and practical attacks,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Robustness of ai-image detectors: Fundamental limits and practical attacks,

Reference 31

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Observation 0cc5a3a7-ac13-478d-ad69-74f2f393d34a · outbound

This paper cites Practical black-box attacks against machine learning,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Practical black-box attacks against machine learning,

Reference 32

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Observation d9f2edc5-93e5-4c3e-8a48-a15b6889f634 · outbound

This paper cites Fakepolisher: Making deepfakes more detection- evasive by shallow reconstruction,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Fakepolisher: Making deepfakes more detection- evasive by shallow reconstruction,

Reference 33

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Observation d8c36b56-418c-444e-8551-484d170b3798 · outbound

This paper cites Cnn- generated images are surprisingly easy to spot... for now,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Cnn- generated images are surprisingly easy to spot... for now,

Reference 34

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Observation 306bfb32-2871-4269-9909-9c038c2ac50f · outbound

This paper cites Diffusion models beat gans on image synthesis,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Diffusion models beat gans on image synthesis,

Reference 35

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Observation 5c3901d4-e381-4f18-b273-cd169a993ba1 · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 36

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Observation 5b7a9ca4-707f-49fc-8040-78a3531bd192 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection High- resolution image synthesis with latent diffusion models,

Reference 37

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Observation 751857d4-50aa-47dd-9eb8-57c127a84670 · outbound

This paper cites Vector quantized diffusion model for text-to-image synthesis,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Vector quantized diffusion model for text-to-image synthesis,

Reference 38

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Observation 1ca5b566-a096-4590-ba0b-0266142b57e1 · outbound

This paper cites Genvidbench: A 6-million benchmark for ai-generated video detection,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Genvidbench: A 6-million benchmark for ai-generated video detection,

Reference 39

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Observation 4f3af3f7-b52d-4400-9afd-b5c58e6d42b2 · outbound

This paper cites Midjourney,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Midjourney,

Reference 40

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source=pdf_text observed=2026-07-11T23:26:36.541592Z digest=sha256:49857e3203f86e83289fdf3db64d1cc2e91e0a21ca7e6f2190b16864f00c982e

Observation c75f1208-caf3-4eb6-9ce9-e198f0e9efed · outbound

This paper cites WuKong-HuaHua,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection WuKong-HuaHua,

Reference 41

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Observation 69245dae-21a7-41e4-bed3-581fc0d25173 · outbound

This paper cites Emerging Properties in Unified Multimodal Pretraining.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Emerging Properties in Unified Multimodal Pretraining

Reference 42

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Observation a7cb8c1a-ba76-44b7-a90b-a90e08b4887c · outbound

This paper cites Flux. 1 kontext: Flow matching for in-context image generation and editing in latent space,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Flux. 1 kontext: Flow matching for in-context image generation and editing in latent space,

Reference 43

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source=pdf_text observed=2026-07-11T23:26:36.541592Z digest=sha256:20c9b95efbda5bf9bda61e2b3b31c36793141c3a891fd777fda19c1272317c6b

Observation 1ec51f29-0099-4b2b-8bbb-beb9703fc51d · outbound

This paper cites OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization Data.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization Data

Reference 44

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Observation c25576cf-c777-47c2-ae11-e8093b42b022 · outbound

This paper cites GPT-4o System Card.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection GPT-4o System Card

Reference 45

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Observation 8c57a911-8a93-4297-bc9d-87a00736459c · outbound

This paper cites Step1X-Edit: A Practical Framework for General Image Editing.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Step1X-Edit: A Practical Framework for General Image Editing

Reference 46

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Observation d8f7439d-d763-4471-b98c-b09d55314465 · outbound

This paper cites Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising,

Reference 47

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Observation b1e1b6d5-067c-4d68-b1b7-b5168ef412f9 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 48

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Observation cebe6e24-7cb7-447e-b495-5aa5dd7044f5 · outbound

This paper cites DINOv3.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection DINOv3

Reference 49

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Observation 48242ad9-e475-4c67-8704-188977a331b1 · outbound

This paper cites Attention is all you need,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Attention is all you need,

Reference 50

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Observation 3cc31346-3178-40d5-a331-798580a9f9aa · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 51

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Observation 5ba23daf-4ae0-48b6-a48e-595e5e8d25d8 · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 52

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Observation e58b7d4d-3034-4e6d-b3ad-b74deeffdfb6 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Lora: Low-rank adaptation of large language models

Reference 53

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Observation 626e2e7a-52d7-4a86-bb8f-df2d992eb130 · outbound

This paper cites Deep residual learning for image recognition,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Deep residual learning for image recognition,

Reference 54

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Observation 80d2475d-b633-4c45-9182-bc4117e24e73 · outbound

This paper cites Xception: Deep learning with depthwise separable convolu- tions,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Xception: Deep learning with depthwise separable convolu- tions,

Reference 55

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Observation 6763027a-eb43-4981-a3c6-e1d48059cce0 · outbound

This paper cites Decoupled weight decay regularization,.

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection Decoupled weight decay regularization,

Reference 56

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